Improving Urban Traffic Speed Prediction Using Data Source Fusion and Deep Learning

Traffic parameter forecasting is critical to effective traffic management but is a challenging task due to the stochasticity of traffic flow characteristics, especially in urban road networks. Traffic networks can be affected by external factors, such as weather, events, accidents, and road construc...

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Bibliographic Details

Published in:	International Conference on Big Data and Smart Computing pp. 1 - 8
Main Authors:	Essien, Aniekan, Petrounias, Ilias, Sampaio, Pedro, Sampaio, Sandra
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.02.2019
Subjects:	Computational modeling Data models data-fusion deep learning intelligent transportation systems (ITS) Long short-term neural networks Mathematical model Meteorology Predictive models Roads Time series analysis traffic data science
ISSN:	2375-9356
Online Access:	Get full text
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